Sensing fabric, method for producing a sensing fabric and method for monitoring based on a sensing fabric

Abstract

The application relates to a sensing fiber cloth, a preparation method thereof and a monitoring method based on the sensing fiber cloth, wherein the sensing fiber cloth comprises a fiber cloth substrate and a nanomaterial functional layer; the nanomaterial functional layer is formed on the fiber cloth substrate through a surface deposition mode; warp yarns of the fiber cloth substrate are conductive warp yarns; the nanomaterial functional layer comprises a piezoresistive sensing unit and a piezoelectric sensing unit; the piezoresistive sensing unit is used for transmitting a resistance change signal through the conductive warp yarns to monitor a polymer substrate curing state and sense a structural strain; the polymer substrate curing state refers to a curing state of a polymer substrate injected into a mold provided with the sensing fiber cloth in a composite material structure preparation process; the composite material structure comprises the sensing fiber cloth and the polymer substrate; and the piezoelectric sensing unit is used for locating a damage position of the composite material structure.

Description

Technical Field

[0001] This application relates to the field of sensing fiber cloth technology, and in particular to sensing fiber cloth, its preparation method and monitoring method based on sensing fiber cloth. Background Technology

[0002] Fiber-reinforced composite materials are increasingly widely used in aerospace, transportation, and other fields due to their high specific strength, high specific modulus, excellent designability, and ease of molding. However, damage to these materials is characterized by its insidious nature and rapid development; if not monitored and warned in a timely manner, it could lead to catastrophic safety accidents. In related technologies, traditional embedded sensors suffer from poor compatibility between the sensor and the composite matrix and are prone to introducing pre-existing defects.

[0003] Currently, no effective solution has been proposed to address the problem of poor compatibility between sensors and composite material matrices in related technologies, which can easily introduce pre-existing defects. Summary of the Invention

[0004] This application provides a sensing fiber cloth and its preparation method, as well as a monitoring method based on the sensing fiber cloth, to at least solve the problems of poor compatibility between sensors and composite material matrices and the easy introduction of pre-existing defects in related technologies.

[0005] In a first aspect, embodiments of this application provide a sensing fiber cloth, comprising: a fiber cloth substrate and a nanomaterial functional layer, wherein the nanomaterial functional layer is formed on the fiber cloth substrate by surface deposition;

[0006] The warp yarns of the fiber fabric matrix are conductive warp yarns;

[0007] The nanomaterial functional layer includes a piezoresistive sensing unit and a piezoelectric sensing unit;

[0008] The piezoresistive sensing unit is used to transmit resistance change signals via the conductive warp yarns to monitor the curing state of the polymer matrix and sense structural strain; the curing state of the polymer matrix refers to the curing state of the polymer matrix injected into the mold on which the sensing fiber cloth is laid during the preparation of the composite material structure; the composite material structure includes the sensing fiber cloth and the polymer matrix;

[0009] The piezoelectric sensing unit is used to locate the damage location of the composite material structure.

[0010] In some embodiments, the weft yarn of the fiber fabric matrix is ​​an insulating weft yarn; the piezoresistive sensing unit and the piezoelectric sensing unit are both arranged on the insulating weft yarn.

[0011] In some embodiments, the nanomaterials of the nanomaterial functional layer are selected from at least one of graphene, carbon nanotubes, carbon black, lead zirconate titanate nanoparticles, barium titanate nanoparticles, and zinc oxide nanowires.

[0012] Secondly, embodiments of this application provide a method for preparing a sensing fiber cloth, the method comprising:

[0013] The fiber fabric matrix is ​​cleaned and chemically activated, and then treated with a silane coupling agent to obtain a pretreated fiber fabric matrix; the warp yarns of the fiber fabric matrix are conductive warp yarns.

[0014] A nanomaterial functional layer is formed on the pretreated fiber cloth substrate by aerosol printing deposition process; the nanomaterial functional layer includes a piezoresistive sensing unit and a piezoelectric sensing unit.

[0015] The fiber cloth substrate with the nanomaterial functional layer deposited is post-processed to obtain the sensing fiber cloth.

[0016] In some embodiments, the post-processing of the fiber fabric substrate with the deposited nanomaterial functional layer to obtain the sensing fiber fabric includes:

[0017] The piezoresistive sensing unit in the fiber cloth matrix with the nanomaterial functional layer deposited is subjected to heat treatment, and the piezoelectric sensing unit in the fiber cloth matrix is ​​subjected to polarization treatment to obtain the sensing fiber cloth.

[0018] Thirdly, embodiments of this application provide a monitoring method based on a sensing fiber cloth, the method comprising:

[0019] Based on the curing process of the sensing fiber cloth and the polymer matrix, a mapping relationship between the degree of curing and the rate of change of resistance is obtained; the sensing fiber cloth is the sensing fiber cloth described in any of the above embodiments; the rate of change of resistance is obtained by measuring the test resistance value of the piezoresistive sensing unit of the sensing fiber cloth based on the conductive warp yarns of the sensing fiber cloth.

[0020] During the composite material structure preparation stage, based on the mapping relationship and the actual resistance value of the piezoresistive sensing unit measured during the preparation process, the curing process of the composite material structure is monitored to obtain curing monitoring results; the composite material structure includes the sensing fiber cloth and the polymer matrix;

[0021] Tensile tests were performed on the obtained composite material structure specimens, and the sensitivity coefficient was obtained by using a standard resistance strain gauge as a reference.

[0022] Based on the aforementioned sensitivity coefficient and the resistance value of the piezoresistive sensing unit of the sensing fiber cloth measured during the application of the composite material structure, the strain distribution of the composite material structure is evaluated to obtain the strain distribution evaluation result.

[0023] Based on the piezoelectric sensing unit of the sensing fiber cloth in the composite material structure, the damage localization result of the composite material structure is obtained.

[0024] Based on the solidification monitoring results, the strain distribution assessment results, and the damage localization results, full life cycle monitoring results are generated.

[0025] In some embodiments, the curing process based on the sensing fiber cloth and polymer matrix, obtaining the mapping relationship between the degree of curing and the rate of change of resistance, includes:

[0026] The sensing fiber cloth is laid into the mold to form a composite material preform sample;

[0027] Injecting the same type of polymer matrix as used in the preparation process into the composite preform sample;

[0028] The degree of curing of the polymer matrix at different times during the curing process is measured, and the rate of change of the test resistance value of the piezoresistive sensing unit measured through the conductive warp is obtained.

[0029] Based on the degree of curing and the rate of change of resistance value at the same time, the mapping relationship between the degree of curing and the rate of change of resistance value is obtained.

[0030] In some embodiments, the tensile test performed on the obtained composite material structure specimen and the sensitivity coefficient obtained using a standard resistance strain gauge as a reference include:

[0031] The obtained composite material structure specimens are installed on a pre-set testing machine, and standard resistance strain gauges are attached to the surface of the composite material structure specimens.

[0032] The composite material structure specimen is stretched at a preset speed using the testing machine, and the strain value of the standard resistance strain gauge and the resistance change rate of the piezoresistive sensing unit measured by a pair of adjacent conductive warp yarns of the sensing fiber cloth are recorded simultaneously to obtain the relationship curve between the strain value and the resistance change rate; based on the relationship curve, the sensitivity coefficient is obtained.

[0033] In some embodiments, the piezoelectric sensing unit based on the sensing fiber cloth in the composite material structure obtains the damage localization result of the composite material structure, including:

[0034] From the piezoelectric sensing units of the sensing fiber cloth in the composite material structure, a target excitation piezoelectric sensing unit is selected, and the other piezoelectric sensing units other than the target excitation piezoelectric sensing unit are used as receiving piezoelectric sensing units.

[0035] An electrical signal is applied to the target excitation piezoelectric sensing unit through the conductive warp yarn, thereby exciting the target excitation piezoelectric sensing unit to emit ultrasonic guided wave signals, and multiple ultrasonic guided wave signal characteristics propagated through the composite material structure are captured by multiple receiving piezoelectric sensing units.

[0036] Based on the characteristics of multiple ultrasonic guided wave signals, the coordinate position of the target excitation piezoelectric sensing unit, and the coordinate position of the receiving piezoelectric sensing unit, the damage localization result of the composite material structure is obtained.

[0037] In some embodiments, obtaining the damage localization result of the composite material structure based on the characteristics of multiple ultrasonic guided wave signals, the coordinate position of the target-excited piezoelectric sensing unit, and the coordinate position of the receiving piezoelectric sensing unit includes:

[0038] Based on the characteristics of multiple ultrasonic guided wave signals, the coordinate position of the target excitation piezoelectric sensing unit, and the coordinate position of the receiving piezoelectric sensing unit, multiple damage imaging maps are obtained according to the delay summation imaging algorithm.

[0039] Multiple damage images are superimposed using an image fusion method to obtain the damage localization result of the composite material structure.

[0040] Compared to related technologies, the sensing fiber cloth and its preparation method, as well as the monitoring method based on the sensing fiber cloth provided in this application, wherein the sensing fiber cloth includes: a fiber cloth matrix and a nanomaterial functional layer, the nanomaterial functional layer being formed on the fiber cloth matrix by surface deposition; the warp yarns of the fiber cloth matrix are conductive warp yarns; the nanomaterial functional layer includes a piezoresistive sensing unit and a piezoelectric sensing unit; the piezoresistive sensing unit is used to transmit resistance change signals via the conductive warp yarns to monitor the curing state of the polymer matrix and sense structural strain; the curing state of the polymer matrix refers to the curing state of the polymer matrix injected into the mold on which the sensing fiber cloth is laid during the composite material structure preparation process; the composite material structure includes the sensing fiber cloth and the polymer matrix; the piezoelectric sensing unit is used to locate the damage location of the composite material structure. Based on this, the problems of poor compatibility between sensors and composite material matrices and the easy introduction of pre-existing defects in related technologies are solved.

[0041] Details of one or more embodiments of this application are set forth in the following drawings and description to make other features, objects and advantages of this application more readily apparent. Attached Figure Description

[0042] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments of this application and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0043] Figure 1 This is a hardware structure block diagram of a monitoring terminal based on a sensing fiber cloth according to an embodiment of this application;

[0044] Figure 2 This is a schematic diagram of a fiber cloth matrix according to an embodiment of this application;

[0045] Figure 3 This is a schematic diagram of any layout of a sensing fiber cloth according to an embodiment of this application;

[0046] Figure 4 This is a microscopic topographic image of a piezoresistive sensing unit according to an embodiment of this application;

[0047] Figure 5 This is a microscopic topographic image of a piezoelectric sensing unit according to an embodiment of this application;

[0048] Figure 6 This is a flowchart of a monitoring method based on a sensing fiber cloth according to an embodiment of this application;

[0049] Figure 7 This is a curing degree curve of the polymer matrix according to an embodiment of this application;

[0050] Figure 8 This is a graph showing the rate of change of resistance value of the piezoresistive sensing unit during the curing process of the polymer matrix according to an embodiment of this application.

[0051] Figure 9 This is a curve showing the relationship between the rate of change of resistance of the piezoresistive sensing unit and the degree of curing of the polymer matrix according to an embodiment of this application.

[0052] Figure 10 This is a graph showing the relationship between the resistance change rate of the piezoresistive sensing unit and the reference strain gauge and strain according to an embodiment of this application.

[0053] Figure 11 This is a diagram showing the damage localization results of a composite material structure using a piezoelectric sensing network according to an embodiment of this application. Detailed Implementation

[0054] To make the objectives, technical solutions, and advantages of this application clearer, the application is described and illustrated below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the application. All other embodiments obtained by those skilled in the art based on the embodiments provided in this application without inventive effort are within the scope of protection of this application. Furthermore, it is understood that although the efforts made in such a development process may be complex and lengthy, for those skilled in the art related to the content disclosed in this application, modifications to design, manufacturing, or production based on the technical content disclosed in this application are merely conventional technical means and should not be construed as insufficient disclosure of the content of this application.

[0055] In this application, the reference to "embodiment" means that a specific feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment that is mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described in this application may be combined with other embodiments without conflict.

[0056] Unless otherwise defined, the technical or scientific terms used in this application shall have the ordinary meaning understood by one of ordinary skill in the art to which this application pertains. The terms “a,” “an,” “an,” “the,” and similar words used in this application do not indicate quantity limitation and may indicate singular or plural. The terms “comprising,” “including,” “having,” and any variations thereof used in this application are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or device that includes a series of steps or modules (units) is not limited to the listed steps or units, but may also include steps or units not listed, or may include other steps or units inherent to these processes, methods, products, or devices. The terms “connected,” “linked,” “coupled,” and similar words used in this application are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. “Multiple” used in this application means two or more. “And / or” describes the relationship between related objects, indicating that three relationships may exist; for example, “A and / or B” can represent: A alone, A and B simultaneously, and B alone. The terms “first,” “second,” “third,” etc., used in this application are merely to distinguish similar objects and do not represent a specific ordering of the objects.

[0057] The method embodiments provided in this example can be executed on a terminal, computer, or similar computing device. Taking running on a terminal as an example, Figure 1 This is a hardware structure block diagram of a monitoring terminal based on a sensing fiber cloth according to an embodiment of this application. Figure 1 As shown, a terminal may include one or more ( Figure 1 Only one is shown in the diagram. A processor 102 (which may include, but is not limited to, a microprocessor MCU or a programmable logic device FPGA, etc.) and a memory 104 for storing data are also shown. Optionally, the terminal may further include a transmission device 106 for communication functions and an input / output device 108. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the terminal described above. For example, the terminal may also include components that are more... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0058] The memory 104 can be used to store computer programs, such as application software programs and modules, like the computer program corresponding to the monitoring method based on sensing fiber cloth in this embodiment. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, thus implementing the above-described method. The memory 104 may include high-speed random access memory and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor 102, and these remote memories can be connected to the terminal via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0059] The transmission device 106 is used to receive or send data via a network. Specific examples of the network described above may include a wireless network provided by the terminal's communication provider. In one example, the transmission device 106 includes a Network Interface Controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the transmission device 106 may be a Radio Frequency (RF) module used for wireless communication with the Internet.

[0060] Fiber-reinforced composite materials are increasingly widely used in military and civilian fields such as aerospace and transportation due to their high specific strength, high specific modulus, excellent designability, and ease of molding. However, this material faces severe challenges in both the preparation and application stages: First, during the preparation process, the uncontrollable state of resin curing can easily lead to defects inside the component, directly affecting its final performance and quality consistency; second, under long-term complex application environments, various hidden damages can easily develop inside the material, which, if not detected in time, may lead to catastrophic accidents.

[0061] To achieve comprehensive structural safety assurance, it is crucial to develop monitoring technologies covering the entire lifecycle from fabrication to application. Existing sensing technologies can be categorized into external and embedded types based on their integration methods. Among these, embedded sensing has attracted significant attention due to its ability to conform to the structure and achieve in-situ perception of internal states. However, the introduction of traditional embedded sensors (such as piezoelectric ceramic sheets and fiber Bragg gratings) may itself become a pre-existing defect, posing a potential threat to structural integrity. This contradiction greatly limits its practical application.

[0062] Therefore, exploring a novel embedded sensing solution that is highly compatible with the main structure, capable of sensing both microscopic physicochemical changes during the fabrication process and diagnosing macroscopic mechanical damage during application, has become a key frontier for ensuring the reliability of advanced composite material structures and achieving their precise intelligent manufacturing. The integrated development of nanomaterials and smart structures provides a new technological approach for this.

[0063] To address the aforementioned issues, this embodiment provides a sensing fiber cloth, comprising: a fiber cloth substrate and a nanomaterial functional layer, wherein the nanomaterial functional layer is formed on the fiber cloth substrate by surface deposition.

[0064] The warp yarns of the fiber fabric matrix are conductive warp yarns;

[0065] The nanomaterial functional layer includes a piezoresistive sensing unit and a piezoelectric sensing unit;

[0066] The piezoresistive sensing unit is used to transmit resistance change signals via conductive warp yarns to monitor the curing state of the polymer matrix and sense structural strain; the curing state of the polymer matrix refers to the curing state of the polymer matrix to be injected into a mold with sensing fiber cloth during the preparation of the composite material structure; the composite material structure includes the sensing fiber cloth and the polymer matrix;

[0067] The piezoelectric sensing unit is used to locate the damage location of the composite material structure.

[0068] Among them, the sensing fiber cloth is a smart material that integrates dual-modal sensing functions. Its core structure consists of a fiber cloth matrix and a nanomaterial functional layer. The two are firmly combined through a precise surface deposition process, which not only ensures the integrity of the structure, but also gives full play to their respective functional characteristics.

[0069] It should be noted that the fiber cloth matrix, as the core carrier of the sensing function and the reinforcing component of the composite material structure, adopts a woven structure design with interlaced warp and weft yarns, in which conductive warp yarns are specifically selected. This conductive warp yarn design cleverly serves a dual purpose: on the one hand, it acts as the structural skeleton of the fiber cloth matrix, interlacing with the weft yarns to form a stable fabric structure, providing the sensing fiber cloth with good mechanical strength and flexibility, ensuring its adaptability to the molding process and service environment of composite materials; on the other hand, it serves as a natural channel for signal transmission, providing a stable and reliable path for the resistance signal transmission of the subsequent piezoresistive sensing unit and the electrical signal excitation and response capture of the piezoelectric sensing unit, eliminating the need for additional complex wiring and simplifying the integration process of the sensing system. Figure 2 This is a schematic diagram of a fiber fabric matrix according to an embodiment of this application. The fiber fabric matrix has a plain weave structure and adopts a warp and weft interlacing weaving method, wherein the longitudinal fibers are conductive warp yarns and the transverse fibers are weft yarns. For example, the conductive warp yarns can be conductive carbon fiber, and the weft yarns can be insulating glass fiber.

[0070] The nanomaterial functional layer is the core of achieving dual-modal sensing functionality. Precisely constructed on a fiber cloth matrix through surface deposition, it integrates piezoresistive and piezoelectric sensing units. These two units, each with its own function, work together to build a monitoring system covering the entire lifecycle of composite materials from preparation to application. The core functions of the piezoresistive sensing unit focus on two key scenarios: first, monitoring the curing state of the polymer matrix, a specialized material (such as resin) injected into a mold pre-laid with the sensing fiber cloth. During the preparation of the composite structure, its degree of curing directly determines the performance and quality consistency of the final product. Based on the piezoresistive effect, the piezoresistive sensing unit can capture the real-time change in its resistance as the curing process progresses and efficiently transmit this signal through conductive warp yarns, thereby achieving dynamic tracking and precise control of the curing process; second, sensing the strain state of the composite structure. During application, when subjected to external loads and deformation, the resistance of the piezoresistive sensing unit changes regularly with strain. Using the resistance change signal transmitted by the conductive warp yarns, the strain distribution and stress conditions of the structure can be deduced. The composite material structure formed by the integrated molding of the sensing fiber cloth and the polymer matrix not only has excellent load-bearing capacity, but also achieves a deep integration of sensing function and structure, fundamentally avoiding the structural defects that may be caused by the introduction of traditional sensors as foreign objects.

[0071] The piezoelectric sensing unit focuses on damage monitoring during the application of composite material structures. Its working principle is based on the direct and inverse piezoelectric effects. After receiving the driving electrical signal through conductive warp yarns, it can stably emit ultrasonic guided waves. When these ultrasonic guided waves propagate within the composite material structure, they exhibit specific signal reflection, diffraction, or attenuation characteristics upon encountering damaged areas. The piezoelectric sensing unit can accurately capture these signal characteristics after propagation through the structure. Combined with preset signal analysis algorithms and the layout information of the sensing unit, it can quickly and accurately identify and locate damage to composite material structures, providing timely and effective early warning support for the safe application of the structure. This forms a complete monitoring solution covering the entire lifecycle of composite material structures from "preparation to application."

[0072] Figure 3 This is a schematic diagram of any layout of a sensing fiber cloth according to an embodiment of this application. Both the piezoresistive sensing unit and the piezoelectric sensing unit are arranged on the transverse weft yarns. The "+" and "-" symbols on the upper and lower edges correspond to the electrode terminals of the conductive warp yarns.

[0073] The sensing fiber cloth provided in the above embodiments combines the fiber cloth matrix with a nanomaterial functional layer deposited on the surface, uses conductive warp yarns as signal transmission channels, and integrates piezoresistive and piezoelectric dual-mode sensing units. This achieves real-time and accurate monitoring of the curing state of the polymer matrix during the composite material structure preparation stage, ensuring the consistency of component quality from the source. Furthermore, during the application stage, it can sense structural strain through the piezoresistive sensing unit and accurately locate damage locations with the help of the piezoelectric sensing unit. This effectively solves the problems of poor compatibility between traditional embedded sensors and composite material matrices, easy introduction of pre-existing defects, and limited functionality. It achieves integrated and comprehensive monitoring of the entire lifecycle of composite material structures from "preparation to application," significantly improving the continuity, accuracy, and reliability of monitoring. Simultaneously, the fiber cloth itself can serve as a distributed sensor network, enabling full-area monitoring of large-area structures, overcoming the monitoring blind spot problem of traditional point sensors. Moreover, the integrated design of the fiber cloth matrix and composite material structure ensures structural integrity, providing key technical support for the safe application of advanced composite materials in aerospace, transportation, and other fields.

[0074] In some embodiments, the weft yarn of the fiber fabric matrix is ​​an insulating weft yarn; the piezoresistive sensing unit and the piezoelectric sensing unit are both arranged on the insulating weft yarn.

[0075] Among them, the weft yarn of the fiber cloth matrix can be designed with insulating material to form an insulating weft yarn. This insulating weft yarn is not only a key component of the warp and weft interlacing structure of the fiber cloth matrix, providing stable mechanical support and good flexibility for the whole, but also serves as a dedicated carrier substrate for sensing functions. Piezoresistive sensing units and piezoelectric sensing units are integrated on this insulating weft yarn through a precise surface deposition process. Moreover, the distribution of the two sensing units does not need to follow a specific rule, which has a very high degree of design and manufacturing freedom. The distribution position, quantity and density can be flexibly adjusted according to the actual application scenario of the composite material and monitoring needs (such as key monitoring areas, monitoring accuracy requirements, etc.) to achieve customized layout.

[0076] In the above embodiments, the free distribution of sensing units without a specific pattern not only breaks through the limitation of fixed unit layout in traditional sensing structures, but also greatly improves the adaptability and flexibility of the technical solution, meeting the personalized monitoring needs of composite materials in different fields such as aerospace and transportation. It also simplifies the preparation process and reduces the customization cost for specific scenarios. At the same time, the insulation properties of the insulating weft yarn effectively avoid signal crosstalk between the piezoresistive and piezoelectric sensing units and the conductive warp yarn, ensuring the stability and accuracy of the two sensing signals. The integrated design of the sensing unit and the insulating weft yarn maintains the structural integrity and mechanical properties of the fiber cloth matrix, and achieves seamless integration of the functional layer and the matrix, providing reliable structural support for the full life cycle monitoring of composite materials, and significantly improving the practicality and engineering application value of the monitoring system.

[0077] In some embodiments, the nanomaterials of the nanomaterial functional layer are selected from at least one of graphene, carbon nanotubes, carbon black, lead zirconate titanate nanoparticles, barium titanate nanoparticles, and zinc oxide nanowires.

[0078] The nanomaterials used in the aforementioned functional layers can be flexibly selected from at least one of graphene, carbon nanotubes, carbon black, lead zirconate titanate nanoparticles, barium titanate nanoparticles, and zinc oxide nanowires, each possessing unique physicochemical properties. Among them, graphene, carbon nanotubes, and carbon black exhibit excellent electrical conductivity and piezoresistive response characteristics, making them suitable as core functional materials for piezoresistive sensing units. Figure 4This is a microscopic morphology diagram of a piezoresistive sensing unit according to an embodiment of this application. It shows a continuously interwoven, porous mesh structure: the nano-conductive materials constituting the unit (such as graphene, carbon nanotubes, etc.) are interconnected in a dense fibrous or aggregated form, forming numerous interconnected network nodes and pores. This structure is the core foundation of the piezoresistive sensing function. When subjected to external forces (such as pressure or strain), the conductive pathways in the mesh structure undergo a "contact-separation" change with deformation, thereby causing a change in resistance and achieving a sensing response to external forces. Simultaneously, the porous mesh morphology enhances the unit's flexibility and deformation adaptability, better conforming to the flexible characteristics of the fiber cloth matrix, and increasing the contact area with the polymer matrix. This strengthens the bonding stability between the sensing unit and the composite material, ensuring reliable performance throughout its entire lifecycle monitoring.

[0079] Lead zirconate titanate nanoparticles and barium titanate nanoparticles, as typical ferroelectric materials, exhibit significant piezoelectric effects, while zinc oxide nanowires, as wurtzite-structured piezoelectric materials, also possess good piezoelectric properties. All three can serve as core functional materials for piezoelectric sensing units. Figure 5 This is a microscopic morphology diagram of a piezoelectric sensing unit according to an embodiment of this application. It shows that the piezoelectric nanomaterials (such as lead zirconate titanate, barium titanate, etc. nanoparticles) are dispersed and distributed. These piezoelectric materials exist in a discrete but locally aggregated form, creating a multiphase distributed microstructure. This structure is the key foundation for the piezoelectric sensing function. When an electrical signal is applied, the piezoelectric material can convert electrical energy into mechanical energy based on the inverse piezoelectric effect, exciting an ultrasonic guided wave signal. When receiving the ultrasonic guided wave, it can convert mechanical energy into an electrical signal through the direct piezoelectric effect to achieve sensing. The discrete distribution ensures the bonding between the piezoelectric material and the matrix, and allows the guided wave signal to propagate and respond effectively in the composite material, adapting to the "single excitation-multiple reception" damage monitoring mode and providing a reliable sensing carrier for damage localization of composite material structures.

[0080] The diversified nanomaterial selection design in the above embodiments not only fully leverages the intrinsic advantages of various materials—carbon-based nanomaterials ensure the high-sensitivity resistance response of the piezoresistive sensing unit, while ferroelectric nanoparticles and zinc oxide nanowires enhance the electromechanical coupling efficiency of the piezoelectric sensing unit, providing reliable material support for the realization of dual-modal sensing functions—but also breaks through the limitations of single-material performance through rich material combination freedom. This allows for targeted optimization of the response speed, detection accuracy, and environmental adaptability of the sensing fiber cloth, meeting the monitoring needs of composite materials under different preparation processes and application environments. Furthermore, the selected nanomaterials all possess good film-forming properties and compatibility, enabling stable adhesion to the fiber cloth matrix through surface deposition processes. This ensures sensing performance without compromising the mechanical flexibility and structural integrity of the matrix, significantly enhancing the practical value and engineering application potential of the sensing fiber cloth.

[0081] This application provides a method for preparing a sensing fiber cloth, the method comprising:

[0082] The fiber fabric matrix is ​​cleaned and chemically activated, and then treated with a silane coupling agent to obtain a pretreated fiber fabric matrix; the warp yarns of the fiber fabric matrix are conductive warp yarns.

[0083] A nanomaterial functional layer is formed on a pretreated fiber cloth substrate using an aerosol printing deposition process; the nanomaterial functional layer includes a piezoresistive sensing unit and a piezoelectric sensing unit.

[0084] The fiber cloth matrix with the deposited nanomaterial functional layer is post-processed to obtain the sensing fiber cloth.

[0085] Specifically, the fiber fabric matrix with conductive warp yarns undergoes a multi-step pretreatment process. This includes sequential cleaning to remove surface oil, impurities, and other contaminants, followed by chemical activation to enhance surface activity and roughness. Subsequently, a silane coupling agent is used to introduce active functional groups onto the matrix surface, resulting in a pretreated fiber fabric matrix with superior adhesion and compatibility. Preferably, the fiber fabric is ultrasonically cleaned sequentially in acetone, anhydrous ethanol, and deionized water for 15-30 minutes each, and then thoroughly dried in an oven. Following this, surface activation is performed. The cleaned fiber fabric is immersed in a 5wt.%~10wt.% sodium hydroxide (NaOH) solution and treated at 60℃~80℃ for 30-60 minutes, generating silanol groups (-Si-OH) on the fiber bundle surface and slightly increasing surface roughness. Finally, a silanization treatment is performed. The activated fiber cloth is immersed in a 1wt.%~5wt.% toluene / deionized water solution and reacted at 60℃~80℃ for 2 to 4 hours. After removal, it is thoroughly washed with ethanol to remove physically adsorbed silane molecules. It is then heat-treated at 80℃~120℃ for 30 to 60 minutes to achieve a strong bond between silane and the fiber cloth matrix.

[0086] Next, an aerosol printing deposition process is used to precisely construct a nanomaterial functional layer containing piezoresistive and piezoelectric sensing units on the pretreated fiber cloth substrate. This process enables high-precision patterned deposition of the sensing units, adapting to the structural characteristics of the fiber cloth substrate. Preferably, the nanocomposite ink is atomized using a pneumatic atomization method, and printing is performed under the following conditions: sheath gas flow rate of 25 sccm~50 sccm, atomizing gas flow rate of 50 sccm~100 sccm, printing platform movement speed of 5 mm / s~10 mm / s, and substrate temperature of 60℃~100℃.

[0087] Finally, the fiber cloth substrate with the deposited nanomaterial functional layer is subjected to targeted post-processing. By optimizing the performance parameters of the sensing unit, a sensing fiber cloth with both structural integrity and dual-modal sensing function is finally obtained.

[0088] The above steps, through sequential cleaning, chemical activation, and silane coupling agent pretreatment of the fiber cloth matrix, effectively enhance the surface activity and compatibility of the matrix. Combined with the high-precision patterning advantages of aerosol printing deposition technology, the precise construction of piezoresistive and piezoelectric dual sensing units on the matrix is ​​achieved. Finally, targeted post-processing optimizes the sensing performance, which not only solves the problems of weak bonding and low distribution accuracy between the sensing units and the fiber cloth matrix in traditional manufacturing processes, but also ensures the stable performance of dual-modal sensing functions. At the same time, it takes into account the structural integrity and mechanical flexibility of the fiber cloth matrix. Ultimately, a sensing fiber cloth with high compatibility with the composite material structure, excellent sensing performance, and controllable manufacturing process is obtained, providing reliable material support for the whole life cycle monitoring of composite materials and laying the technological foundation for the engineering application of this type of intelligent sensing material.

[0089] In some embodiments, the post-processing of the fiber fabric substrate with the deposited nanomaterial functional layer to obtain the sensing fiber fabric includes:

[0090] The piezoresistive sensing unit in the fiber cloth matrix with the nanomaterial functional layer deposited is subjected to heat treatment, and the piezoelectric sensing unit in the fiber cloth matrix is ​​subjected to polarization treatment to obtain the sensing fiber cloth.

[0091] Among them, differentiated treatment is carried out for the characteristics of different sensing units in the functional layer: targeted heat treatment is carried out on the piezoresistive sensing units in the nanomaterial functional layer on the fiber cloth matrix. By precisely controlling the heating temperature and holding time (e.g., holding at 80℃~120℃ for 1 hour to 2 hours), the residual solvent in the piezoresistive sensing unit is fully volatilized, the conductive path and structural stability of the nanomaterial are optimized, and its piezoresistive response sensitivity and signal consistency are improved.

[0092] Meanwhile, the piezoelectric sensing unit of the nanomaterial functional layer in the fiber cloth matrix is ​​subjected to professional polarization treatment. It is kept at a preset time (e.g., 30 minutes to 60 minutes) under a specific temperature environment (e.g., 150℃~160℃) and electric field strength (e.g., 50V / μm~150V / μm), and slowly cooled to room temperature while maintaining the electric field, so as to induce and lock the piezoelectric properties and ensure that it has the ability to efficiently transmit and receive ultrasonic guided waves. Through the synergistic implementation of the above two types of targeted post-processing, a sensing fiber cloth with excellent sensing performance and stable and reliable function is finally obtained.

[0093] The above post-processing steps, through targeted heat treatment of the piezoresistive sensing unit, optimized the conductive path and structural stability of the nanomaterial, significantly improving the sensitivity, signal consistency, and long-term reliability of the piezoresistive sensing. Simultaneously, specialized polarization treatment of the piezoelectric sensing unit successfully induced and locked its piezoelectric properties, ensuring its ability to efficiently transmit and receive ultrasonic guided waves. The synergistic effect of these two differentiated treatments maximized the core performance of the dual-mode sensing unit while ensuring a firm bond between the sensing unit and the fiber cloth matrix, preventing functional layer detachment or performance degradation. Ultimately, a sensing fiber cloth with high sensing accuracy, strong stability, and reliable functional synergy was obtained, providing crucial performance assurance for the full life-cycle monitoring of composite materials and further enhancing the compatibility and integrated adaptability of the sensing fiber cloth with the composite material structure.

[0094] This application provides a monitoring method based on sensing fiber cloth. Figure 6 This is a flowchart of a monitoring method based on a sensing fiber cloth according to an embodiment of this application. The process includes the following steps:

[0095] Step S601: Based on the curing process of the sensing fiber cloth and the polymer matrix, a mapping relationship between the degree of curing and the rate of change of resistance is obtained; the sensing fiber cloth is the sensing fiber cloth of any of the above embodiments; the rate of change of resistance is obtained by measuring the test resistance value of the piezoresistive sensing unit of the sensing fiber cloth based on the conductive warp of the sensing fiber cloth.

[0096] Specifically, before the formal fabrication of the composite material structure, the sensing fiber cloth conforming to the above embodiment is first cut to a suitable size and laid into a special mold to form a composite material preform sample. A polymer matrix of the same type as the one actually being prepared is then injected into the mold. Subsequently, using standard testing equipment such as differential scanning calorimetry (DSC), the degree of curing of the polymer matrix at different curing times is measured in real time. Simultaneously, the conductive warp yarns in the sensing fiber cloth serve as a stable signal transmission channel. High-precision digital multimeters and other testing instruments are used to collect the initial resistance value of the piezoresistive sensing unit and the test resistance value at each curing time. The rate of change of the test resistance value is obtained by calculating the ratio of the difference between the test resistance value and the initial resistance value to the initial resistance value. Finally, the degree of curing and the rate of change of the test resistance value at the same time are correlated one-to-one. Through mathematical processing methods such as data fitting and regression analysis, a stable and reliable quantitative mapping relationship between the two is established, providing a scientific and effective data model support for the subsequent composite material structure fabrication stage by using the resistance signal to infer the curing state in real time.

[0097] In step S602, during the composite material structure preparation stage, based on the mapping relationship and the actual resistance value of the piezoresistive sensing unit measured during the preparation process, the curing process of the composite material structure is monitored to obtain curing monitoring results; the composite material structure includes sensing fiber cloth and polymer matrix.

[0098] Specifically, in the composite material structure preparation stage (i.e., the formal production stage), based on the quantitative mapping relationship established in the early stage by testing the degree of curing and the rate of change of resistance value at the same time, combined with the actual resistance value of the piezoresistive sensing unit obtained in real time through the conductive warp yarn of the sensing fiber cloth during the preparation process, the actual resistance value change rate at the corresponding time is first calculated, and then the real-time degree of curing of the polymer matrix in the composite material structure is obtained by back-calculating through this mapping relationship, thereby realizing dynamic tracking and precise monitoring of the curing process; at the same time, by monitoring the stability and trend of resistance value changes in real time, problems such as abnormal temperature rise, insufficient glue, and bubbles that may occur during the curing process can be identified in a timely manner, and finally, a curing monitoring result covering key information such as curing progress, curing uniformity, and the presence of defects is formed, providing a real-time and reliable basis for process adjustment and quality control in the preparation process, and ensuring the preparation quality and performance consistency of the composite material structure from the source.

[0099] Step S603: Perform a tensile test on the obtained composite material structure specimen and obtain the sensitivity coefficient using a standard resistance strain gauge as a reference.

[0100] Specifically, after obtaining the curing monitoring results and before the application stage, a composite material structure sample that has completed curing and is embedded with the aforementioned sensing fiber cloth is selected for a tensile test. A standard resistance strain gauge is used as a reference to obtain the sensitivity coefficient. For example, one method for obtaining the sensitivity coefficient is as follows: the sample is precisely installed in a preset universal testing machine fixture, and a standard resistance strain gauge with sufficient accuracy is attached to the sample surface at the position corresponding to the piezoresistive sensing unit as a calibration reference. Subsequently, the axial tension is applied to the sample by the testing machine at a preset constant tensile speed. During the tensile process, the data acquisition system is simultaneously activated. On the one hand, the accurate strain value fed back by the standard resistance strain gauge is recorded in real time. On the other hand, the resistance data of the piezoresistive sensing unit is continuously collected and the resistance change rate is calculated through a pair of adjacent conductive warp yarns in the sensing fiber cloth as a signal transmission channel. Based on the collected multiple sets of synchronous strain values ​​and resistance change rate data, a relationship curve between the two is plotted. After linear fitting of the curve, the slope of the fitted straight line is the sensitivity coefficient of the piezoresistive sensing unit, providing key quantitative parameter support for inferring the structural strain state from the resistance signal in the subsequent application stage of the composite material structure.

[0101] Step S604: Based on the sensitivity coefficient and the resistance value of the piezoresistive sensing unit of the sensing fiber cloth measured during the application of the composite material structure, the strain distribution of the composite material structure is evaluated to obtain the strain distribution evaluation result.

[0102] Specifically, in the application stage of composite material structures, based on the sensitivity coefficient of the piezoresistive sensing unit obtained through tensile tests and standard resistance strain gauge calibration in the early stage, and combined with the actual resistance value of the piezoresistive sensing unit measured in real time through the conductive warp yarns of the sensing fiber cloth during the application process, the resistance change rate is first calculated by the resistance change and the initial resistance value. Then, based on the correspondence between the sensitivity coefficient and the resistance change rate, the real-time strain data of each monitoring area of ​​the structure is deduced. Furthermore, the overall strain distribution state of the composite material structure is determined by the integrated analysis of strain data from multiple areas. At the same time, combined with the load characteristics of the application scenario and the strain change law over time, the type, magnitude and duration of the loads borne by the structure during the application process are traced to complete the accurate assessment of the load history. Finally, a comprehensive evaluation result covering the real-time strain distribution of the structure, the stress state of key areas and the load history of the entire application cycle is obtained, providing accurate data support for the performance degradation analysis, remaining life prediction and maintenance strategy optimization of the structure.

[0103] Step S605: Based on the piezoelectric sensing unit of the sensing fiber cloth in the composite material structure, the damage localization result of the composite material structure is obtained.

[0104] In the application stage of composite material structures, damage localization results can be obtained based on the piezoelectric sensing units of the sensing fiber cloth within the composite material structure. For example, one specific process for obtaining damage localization results can be as follows: Based on multiple piezoelectric sensing units integrated within the sensing fiber cloth embedded in the composite material structure, one is selected as the target excitation piezoelectric sensing unit, and the remaining piezoelectric sensing units are used as receiving piezoelectric sensing units, constructing a "single excitation-multiple receiving" sensing network layout; subsequently, an electrical signal with preset parameters is applied to the target excitation piezoelectric sensing unit through the longitudinal conductive warp yarns in the sensing fiber cloth, exciting it to stably emit ultrasonic guided wave signals based on the inverse piezoelectric effect. These ultrasonic guided waves propagate throughout the entire interior of the composite material structure, and if they encounter a damaged area, they will generate… Characteristic changes such as diffraction and scattering are synchronously captured by multiple receiving piezoelectric sensing units, which capture the ultrasonic guided wave signal characteristics after propagation through the structure. Then, combined with the pre-calibrated target-excited piezoelectric sensing unit and the coordinate positions of each receiving piezoelectric sensing unit, the time difference and corresponding distance of the ultrasonic guided wave under different propagation paths are calculated according to the delay summation imaging algorithm, resulting in multiple sets of imaging maps of possible damage areas. Finally, these damage imaging maps are superimposed using an image fusion method, effectively eliminating blind spots and errors of a single monitoring path, accurately identifying the specific location of damage in the composite material structure, and thus obtaining accurate and reliable damage localization results.

[0105] Step S606: Based on the solidification monitoring results, strain distribution assessment results, and damage location results, generate full life cycle monitoring results.

[0106] Specifically, based on the curing monitoring results obtained through piezoresistive sensing units during the composite material structure preparation stage, the strain distribution assessment results obtained through analysis of the sensitivity coefficient and real-time resistance value of the piezoresistive sensing units during the application stage, and the damage location results accurately identified by piezoelectric sensing units, the system integrates the entire process status information of the structure from preparation and curing to long-term application through cross-validation, collaborative analysis, and deep fusion of multi-source data. It clearly presents the intrinsic relationship between curing defects and application damage, the evolution trajectory of structural performance, and the changing laws of key performance parameters. Finally, it generates complete monitoring results covering the entire life cycle of "preparation-application", providing comprehensive, accurate, and coherent technical basis for the quality traceability, maintenance decisions (such as the determination of the timing and scope of damage repair), and remaining life assessment of composite material structures, effectively ensuring the safe and reliable operation of the structure throughout its entire life cycle.

[0107] Through steps S601 to S606, the curing degree and resistance change rate mapping relationship established during the curing process of the sensing fiber cloth and polymer matrix are utilized. Combined with the actual resistance value monitoring of the piezoresistive sensing unit during the preparation stage, the curing process of the composite material structure is accurately controlled, ensuring the consistency of preparation quality. Furthermore, the sensitivity coefficient is obtained through tensile testing and calibration with standard resistance strain gauges. Based on this coefficient and the resistance value data of the piezoresistive sensing unit during the application stage, the structural strain distribution is accurately assessed. Simultaneously, the ultrasonic guided wave transmission and reception function of the piezoelectric sensing unit is used to accurately locate the damage location of the composite material structure. Finally, the three core results of curing monitoring, strain distribution assessment, and damage location are integrated to generate complete monitoring data covering the entire life cycle of "preparation-application". This not only solves the problems of poor compatibility between traditional embedded sensors and composite material matrices and the easy introduction of pre-existing defects, but also realizes comprehensive and collaborative monitoring of static strain, dynamic damage, and preparation process of composite material structures. This provides comprehensive and reliable technical support for structural quality traceability, maintenance decisions, and life assessment, significantly improving the continuity, accuracy, and engineering application value of composite material structure monitoring.

[0108] In some embodiments, the curing process based on the sensing fiber cloth and polymer matrix, obtaining the mapping relationship between the degree of curing and the rate of change of resistance, includes:

[0109] The sensing fiber cloth is laid into the mold to form a composite material preform sample;

[0110] Injecting the same type of polymer matrix as used in the preparation process into the composite preform sample;

[0111] The degree of curing of the polymer matrix at different times during the curing process is measured, and the rate of change of the test resistance value of the piezoresistive sensing unit measured through the conductive warp is obtained.

[0112] Based on the degree of curing and the rate of change of resistance value at the same time, the mapping relationship between the degree of curing and the rate of change of resistance value is obtained.

[0113] Specifically, before the formal fabrication (production) of the composite material structure, the sensing fiber cloth conforming to any of the above embodiments is first precisely cut to ensure its size is perfectly matched to the mold cavity. Then, the sensing fiber cloth is laid flat into a dedicated mold to form a composite material preform sample with a regular structure and tight interlayer bonding. The selected sensing fiber cloth uses a fiber cloth matrix with conductive warp yarns and insulating weft yarns as a carrier. Piezoresistive sensing units and piezoelectric sensing units are integrated through a surface deposition process. The nanomaterials in the nanomaterial functional layer are selected from at least one of graphene, carbon nanotubes, carbon black, lead zirconate titanate nanoparticles, barium titanate nanoparticles, and zinc oxide nanowires. These nanomaterials possess both structural reinforcement and dual-modal sensing functions, ensuring that the preform's integrity is not compromised after laying, while also providing a structural foundation for subsequent full life-cycle monitoring.

[0114] After laying up the sensing fiber cloth and forming a composite preform sample with a regular structure and tight interlayer bonding, a polymer matrix (such as a resin material) of the same type as the actual material to be prepared needs to be precisely injected into the mold. The injection process requires strict control of the injection speed, pressure, and injection volume to ensure that the polymer matrix can uniformly penetrate into the gaps between the fibers of each layer of the preform sample, fully encapsulating the sensing fiber cloth and avoiding defects such as air bubbles and insufficient adhesive due to improper injection. It should be noted that the selection of the polymer matrix must ensure that its curing characteristics and mechanical properties are completely consistent with the actual production scenario. This lays the foundation for subsequent precise monitoring of the curing process through the piezoresistive sensing unit of the sensing fiber cloth, establishing a reliable mapping relationship between the degree of curing and the rate of change of resistance value, and ensuring the quality of the composite structure preparation and the accuracy of the monitoring data.

[0115] During the curing process, it is necessary to measure the degree of curing of the polymer matrix at different times and obtain the rate of change of the test resistance value of the piezoresistive sensing unit measured through conductive warp yarns. The degree of curing can be measured using standard testing methods such as differential scanning calorimetry (DSC) to measure the degree of curing of the polymer matrix in real time at different times, accurately capturing the progress and extent of the curing reaction. Figure 7 This is a curing degree curve of the polymer matrix according to an embodiment of this application. The graph shows the curing degree of the polymer matrix as a function of curing time. The vertical axis represents the curing degree (a quantitative indicator of the curing reaction process of the polymer matrix, usually a value between 0 and 1, where 0 represents that the polymer matrix is ​​not cured at all and 1 represents that the polymer matrix is ​​completely cured). The horizontal axis is the curing time, in minutes.

[0116] Simultaneously, using the conductive warp yarns in the sensing fiber cloth as a signal transmission channel, the resistance data of the piezoresistive sensing unit is continuously collected using testing equipment such as a high-precision digital multimeter. First, the initial resistance value of the piezoresistive sensing unit is recorded. Then, combined with the real-time test resistance values ​​at different curing times, the ratio of the resistance change to the initial resistance value is calculated to obtain the rate of change of the test resistance value of the sensing fiber cloth. This enables synchronous monitoring of the piezoresistive signal response during the curing process of the polymer matrix. Figure 8 This is a graph showing the rate of change of resistance of the piezoresistive sensing unit during the curing process of the polymer matrix according to an embodiment of this application. The graph shows the change of resistance of the piezoresistive sensing unit with curing time during the curing process of the polymer matrix. The vertical axis is the rate of change of resistance (representing the relative change between the real-time resistance and the initial resistance), and the horizontal axis is the curing time (minutes).

[0117] Subsequently, the test curing degree data and the test resistance change rate data measured at the same time point were correlated one-to-one. Through mathematical processing methods such as data fitting and regression analysis, a stable and reliable quantitative mapping relationship between the two was established. This mapping relationship can accurately reflect the inherent correlation between the curing degree of the polymer matrix and the resistance response change of the piezoresistive sensing unit, providing scientific and effective data model support for the subsequent composite material structure preparation stage to infer the curing state in real time through the resistance signal. Figure 9 This is a curve showing the relationship between the resistance change rate of the piezoresistive sensing unit and the curing degree of the polymer matrix according to an embodiment of this application. The horizontal axis represents the resistance change rate, and the vertical axis represents the curing degree.

[0118] In some embodiments, the tensile test performed on the obtained composite material structure specimen and the sensitivity coefficient obtained using a standard resistance strain gauge as a reference include:

[0119] The obtained composite material structure specimens are installed on a pre-set testing machine, and standard resistance strain gauges are attached to the surface of the composite material structure specimens.

[0120] The composite material structure specimen is stretched at a preset speed using the testing machine, and the strain value of the standard resistance strain gauge and the resistance change rate of the piezoresistive sensing unit measured by a pair of adjacent conductive warp yarns of the sensing fiber cloth are recorded simultaneously to obtain the relationship curve between the strain value and the resistance change rate; based on the relationship curve, the sensitivity coefficient is obtained.

[0121] Specifically, after obtaining the curing monitoring results and before the application stage, a composite material structure sample that has been cured and molded is selected and precisely installed in a preset universal testing machine fixture to ensure accurate positioning and uniform stress on the sample. At the same time, a standard resistance strain gauge with qualified accuracy is pasted on the surface of the composite material structure sample at the position corresponding to the piezoresistive sensing unit of the sensing fiber cloth as a calibration reference.

[0122] Subsequently, an axial tensile force is applied to the specimen using a testing machine at a preset constant tensile speed (e.g., 1 mm / min). During the tensile process, a data acquisition system is simultaneously activated to record the precise strain value fed back by the standard resistance strain gauge in real time, as well as the resistance change rate of the piezoresistive sensing unit measured by a pair of adjacent conductive warp yarns of the sensing fiber cloth. Based on the collected multiple sets of synchronous data, a curve showing the relationship between strain value and resistance change rate is plotted. The curve is then linearly fitted, and the slope of the fitted straight line is the sensitivity coefficient of the piezoresistive sensing unit. This provides key performance parameter support for inferring the structural strain state from the resistance signal in subsequent application stages. Figure 10 This is a graph showing the relationship between the resistance change rate of the piezoresistive sensing unit and the strain of the reference strain gauge according to an embodiment of this application. The horizontal axis represents the strain value, the vertical axis represents the resistance change rate, the solid line represents the response curve of the piezoresistive sensing unit, and the dashed line represents the response curve of the standard strain gauge.

[0123] The above steps ensured the measurement accuracy and reliability of the sensitivity coefficient through the calibration of standard strain gauges, providing key quantitative parameters to support the subsequent application stage by inferring the structural strain state through resistance signals. Furthermore, by coordinating the measurement with the conductive warp yarns of the sensing fiber cloth, the sensitivity coefficient and the sensing system were precisely matched, avoiding deviations between external measurements and actual application scenarios. This significantly improved the accuracy and reliability of subsequent strain monitoring and further perfected the technical chain of full life cycle monitoring.

[0124] In some embodiments, the piezoelectric sensing unit based on the sensing fiber cloth in the composite material structure obtains the damage localization result of the composite material structure, including:

[0125] From the piezoelectric sensing units of the sensing fiber cloth in the composite material structure, a target excitation piezoelectric sensing unit is selected, and the other piezoelectric sensing units other than the target excitation piezoelectric sensing unit are used as receiving piezoelectric sensing units.

[0126] An electrical signal is applied to the target excitation piezoelectric sensing unit through the conductive warp yarn, thereby exciting the target excitation piezoelectric sensing unit to emit ultrasonic guided wave signals, and multiple ultrasonic guided wave signal characteristics propagated through the composite material structure are captured by multiple receiving piezoelectric sensing units.

[0127] Based on the characteristics of multiple ultrasonic guided wave signals, the coordinate position of the target excitation piezoelectric sensing unit, and the coordinate position of the receiving piezoelectric sensing unit, the damage localization result of the composite material structure is obtained.

[0128] Specifically, in the application stage of composite material structures, when monitoring damage to the composite material structure, one of the multiple piezoelectric sensing units integrated by the sensing fiber cloth embedded in the structure is randomly selected as the target excitation piezoelectric sensing unit, while all the remaining piezoelectric sensing units are set as receiving piezoelectric sensing units, forming a "single excitation-multiple receiving" sensing network layout.

[0129] Subsequently, using the conductive warp yarns of the sensing fiber cloth as a signal transmission channel, an electrical signal with preset parameters (such as a five-cycle Hanning window modulated sinusoidal signal with a center frequency of 150 kHz) is applied to the target-excited piezoelectric sensing unit. Based on the inverse piezoelectric effect, the target-excited piezoelectric sensing unit is excited to emit a stable ultrasonic guided wave signal, which propagates throughout the composite material structure. During propagation, if there is damage to the structure, the guided wave will undergo diffraction and scattering. Multiple receiving piezoelectric sensing units simultaneously capture the ultrasonic guided wave signal after propagation through the composite material structure, thereby obtaining multiple ultrasonic guided wave signal features containing damage information, providing basic data support for subsequent damage identification and localization.

[0130] When identifying and locating damage in composite material structures, based on the characteristics of multiple ultrasonic guided wave signals captured by multiple receiving piezoelectric sensing units and propagating through the composite material structure, and combined with the pre-calibrated coordinate positions of the target excitation piezoelectric sensing units and the coordinate positions of each receiving piezoelectric sensing unit, the delay summation imaging algorithm is used to calculate the matching relationship between the time difference and the corresponding distance of the ultrasonic guided waves under different propagation paths. This constructs an elliptical or quasi-elliptical potential damage region with the excitation unit and the receiving unit as the focus. Then, the multiple sets of damage region images formed by all piezoelectric sensing units in the sensing fiber cloth are fused and processed to effectively superimpose multi-path monitoring information, eliminate blind spots and errors of a single monitoring path, and finally accurately identify the specific location of damage in the composite material structure, realizing quantitative and visual localization of structural damage.

[0131] The above steps construct a "single excitation-multiple receiver" piezoelectric sensing network layout, using conductive warp yarns as a stable signal transmission channel. An electrical signal is applied to the target excitation piezoelectric sensing unit to excite ultrasonic guided wave signals. Multiple receiving piezoelectric sensing units accurately capture the characteristics of the ultrasonic guided wave signals propagating through the composite material structure. Combining the coordinate positions of the target excitation and receiving piezoelectric sensing units, damage localization results are obtained through professional algorithm analysis. This not only achieves accurate identification and localization of damage to composite material structures, filling the monitoring blind spots of traditional point sensors, but also avoids structural compatibility issues caused by introducing additional sensors due to the integrated design of the sensing unit and the fiber cloth matrix. This significantly improves the comprehensiveness, accuracy, and engineering practicality of damage monitoring, providing reliable technical support for safety early warning and maintenance decisions during the service life of composite material structures.

[0132] In some embodiments, obtaining the damage localization result of the composite material structure based on the characteristics of multiple ultrasonic guided wave signals, the coordinate position of the target-excited piezoelectric sensing unit, and the coordinate position of the receiving piezoelectric sensing unit includes:

[0133] Based on the characteristics of multiple ultrasonic guided wave signals, the coordinate position of the target excitation piezoelectric sensing unit, and the coordinate position of the receiving piezoelectric sensing unit, multiple damage imaging maps are obtained according to the delay summation imaging algorithm.

[0134] Multiple damage images are superimposed using an image fusion method to obtain the damage localization result of the composite material structure.

[0135] Specifically, based on the characteristics of the ultrasonic guided wave signal after propagation through the composite material structure captured by multiple receiving piezoelectric sensing units, and combined with the pre-calibrated coordinate positions of the target excitation piezoelectric sensing unit and each receiving piezoelectric sensing unit, the time difference of the ultrasonic guided wave along the "excitation unit-damage-receiving unit" path and the direct "excitation unit-receiving unit" path is calculated using a delay summation imaging algorithm. By combining the matching relationship between waveguide group velocity and propagation distance, an elliptical or quasi-elliptical potential damage region is constructed for each pair of excitation-receiver sensing units, with the two units as foci. This yields multiple damage images corresponding to different sensing unit pairs. Subsequently, these damage images are superimposed using image fusion methods to accurately identify the specific location and extent of damage in the composite material structure, obtaining accurate, reliable, and visualized damage localization results. The damage location can be determined by the following formula:

[0136] ;

[0137] in, ; ; ;

[0138] In the above formula, the subscripts A, D, and R represent the excitation piezoelectric sensing unit (Actuator), damage (Damage), and receiving piezoelectric sensing unit (Receiver), respectively, where t A-D-R The time it takes for the ultrasonic guided wave to propagate from the excitation piezoelectric sensing unit to the damage and then to the receiving piezoelectric sensing unit; t A-R v1 is the time it takes for the ultrasonic guided wave to propagate from the excitation piezoelectric sensing unit to the receiving piezoelectric sensing unit; v2 is the group velocity of the guided wave excited by the excitation piezoelectric sensing unit; v3 is the group velocity of the damage-induced scattered guided wave; L A-D To excite the piezoelectric sensing unit (x A ,y A ) and damage (x D ,y D The distance LD-R For damage (x) D ,y D ) and receiving piezoelectric sensing unit (x R ,y R The distance L A-R To excite the piezoelectric sensing unit (x A ,y A ) and receiving piezoelectric sensing unit (x R ,y R ( ) distance.

[0139] Given the excitation piezoelectric sensing unit (x) A ,y A ) and receiving piezoelectric sensing unit (x R ,y R The position of ) The damage can be determined by the ultrasonic guided wave signal captured by the piezoelectric sensing unit network of the sensing fiber cloth. Given that v1 and v2 are known through theoretical analysis or experimental measurement, the damage is located on an ellipse or quasi-ellipse with the excitation and receiving piezoelectric sensing units as foci. By fusing images constructed from the paths of all piezoelectric sensing units in the sensing fiber cloth using image fusion methods, a superimposed image of the damage location determined by all piezoelectric sensing units in the entire sensing fiber cloth can be obtained, enabling quantitative monitoring of the damage. Figure 11 This diagram illustrates the damage localization results of a composite material structure using a piezoelectric sensing network according to an embodiment of this application. The horizontal and vertical axes represent the spatial location of the structure (in mm). The distributed dashed rectangles identify piezoelectric sensing units, and the small ellipses marked "True Damage Location" represent software-generated damage localization areas. The diagram utilizes the "single-excitation-multiple-receiver" mode of the piezoelectric sensing units to acquire the ultrasonic guided wave signal characteristics after propagation through the structure. Combining a delay summation imaging algorithm and an image fusion method, elliptical markers are ultimately generated at the true damage locations, visually representing the spatial distribution of the damage. This result verifies the accurate damage localization capability of the piezoelectric sensing network and clarifies the damage range through the visualized elliptical areas, providing an intuitive and reliable spatial location basis for damage warning and maintenance decisions during the application phase of composite material structures.

[0140] The above steps fully utilize the ultrasonic guided wave signal characteristics captured by multiple receiving piezoelectric sensing units, combine the precise coordinate positions of the target excitation piezoelectric sensing unit and each receiving piezoelectric sensing unit, and construct corresponding damage imaging maps for each pair of excitation-receiver sensing units using a delay summation imaging algorithm. Then, multiple damage imaging maps are superimposed and integrated using an image fusion method, effectively fusing multi-path monitoring information. This eliminates blind spots and errors that may exist in a single monitoring path, enhances the signal characteristics of the damaged area, and achieves accurate identification and range definition of damage locations in composite material structures. At the same time, relying on the integrated design of the sensing fiber cloth and the composite material structure, it avoids compatibility issues caused by the introduction of additional sensors, significantly improving the accuracy, reliability, and visualization of damage monitoring, and providing strong technical support for safety early warning and maintenance decisions during the service life of composite material structures.

[0141] In some embodiments, the fiber fabric matrix is ​​a plain-weave carbon fiber / glass fiber hybrid fabric, with T300 grade 3K carbon fiber as the warp yarn and E-glass glass fiber as the weft yarn; the chemical reagents include acetone, anhydrous ethanol, sodium hydroxide, and APTES silane coupling agent; in terms of nanomaterials, the piezoresistive sensing unit ink uses a carbon nanotube dispersion with a concentration of 0.05 mg / mL, and the piezoelectric sensing unit ink uses a piezoelectric nanocomposite material (PZT / P(VDF-TrFE)) dispersion with a concentration of 0.075 mg / mL; the experimental equipment includes an ultrasonic cleaner, an aerosol jet printing system, a polarization device, and a vacuum oven.

[0142] The fiber cloth matrix was first pretreated by ultrasonically cleaning it in acetone, ethanol, and deionized water for 20 minutes each and then drying it. Then it was activated by immersing it in 8wt.% NaOH solution at 70℃ for 40 minutes, rinsing it with deionized water until neutral, and then drying it. Then it was silanized by immersing it in 2wt.% APTES / ethanol solution at 70℃ for 3 hours, rinsing it with ethanol, and then curing it at 110℃ for 1 hour.

[0143] Next, the functional layer was constructed. Piezoresistive sensing unit ink was first printed on the odd-numbered weft yarns using an aerosol printing system. The sheath airflow was set to 40 sccm, the atomizing airflow to 80 sccm, the printing speed to 8 mm / s, and the substrate temperature to 80°C. After drying, piezoelectric sensing unit ink was printed on the even-numbered weft yarns. The parameters were adjusted to sheath airflow to 50 sccm, the atomizing airflow to 90 sccm, the printing speed to 8 mm / s, and the substrate temperature to 80°C.

[0144] Finally, post-processing was performed. The fiber cloth of the deposited piezoelectric unit was heat-treated at 100°C for 1.5 hours. The fibers of the deposited piezoelectric unit were then arranged on the grounded stage of the polarization device, heated to 155°C, and subjected to an electric field of 100V / μm. After holding for 45 minutes, the mixture was slowly cooled to room temperature at a rate of 3°C / min while maintaining the electric field. The final result was as follows: Figure 4 The SEM image (scanning electron microscope image) shows the morphology of the nanomaterials on the fiber surface of the piezoresistive sensing unit. The nanomaterials are uniformly distributed, ensuring the good piezoresistive response performance of the piezoresistive sensor, and as shown... Figure 5 The image shows a SEM image of the piezoelectric composite material morphology on the fiber surface of the piezoelectric sensing unit, and based on d 33 Test results demonstrate the excellent piezoelectric performance (d) of the piezoelectric sensing unit. 33 Test results are core indicators for measuring the strength of piezoelectric properties in piezoelectric materials.

[0145] In some embodiments, the sensing fiber cloth is cut and laid into a mold as a layer of reinforcing fiber cloth to prepare a fiber-reinforced composite laminate. At the same time, the exposed ends of the carbon fiber warp yarns in the sensing fiber cloth, which serve as wires, are used as electrodes and connected to a high-precision digital multimeter through leads. The laminate is then placed in an autoclave, and the degree of curing of the same batch of resin is calibrated simultaneously using a differential scanning calorimeter (DSC).

[0146] The test procedure followed the standard epoxy resin curing process: heating to 130°C at a rate of 2°C / min, holding at that temperature for 2 hours, and then cooling to 60°C at a rate of 2°C / min. Throughout the curing process, the rate of change of resistance k(t) of the piezoresistive sensing unit on the sensing fiber cloth was recorded in real time (see [link to relevant documentation]). Figure 8 ) and the degree of cure, DoC(t), measured by DSC (see [reference]). Figure 7 );Will Figure 7 and Figure 8 After data association, we get Figure 9 The calibration curves of the resistance change rate k and the degree of cure DoC shown are fitted to obtain the quantitative relationship formula DoC=-1.43k. This formula clarifies the correspondence between the resistance change of the piezoresistive sensing unit and the degree of resin cure, providing a reliable quantitative basis for real-time and accurate monitoring of the resin curing process in the composite material structure preparation stage.

[0147] In some embodiments, a composite material structure specimen containing a piezoresistive sensing unit is mounted on a universal testing machine. A standard resistance strain gauge is attached to the specimen surface as a reference. After connecting a multimeter, the specimen is stretched at a speed of 1 mm / min, and the strain ε and the resistance R of the piezoresistive sensing unit are recorded simultaneously, yielding results as shown below. Figure 10The curve showing the relationship between the rate of change of resistance and strain, after fitting, determined the sensitivity factor (Gauge Factor) of the piezoresistive sensing unit to be 30.2.

[0148] Subsequently, damage identification and localization tests were conducted. First, a composite laminate of sensing fiber cloth was prepared, and a Teflon film was pre-placed within the laminate to create artificial delamination defects. Then, using active guided wave monitoring, one piezoelectric sensing unit was selected as the exciter, and a five-cycle Hanning window modulated sinusoidal ultrasonic guided wave signal with a center frequency of 150 kHz was applied to it. The remaining piezoelectric sensing units acted as receivers to receive the guided wave signals propagating through the structure. Based on a pre-set delay-summing imaging algorithm, the received signals were analyzed and processed to generate damage images, such as... Figure 11 As shown, by comparing the actual damage location with the imaging-predicted damage area, it was verified that the dual-modal sensing fiber cloth has good strain monitoring reliability and damage location accuracy in the application stage of composite material structures.

[0149] Furthermore, in conjunction with the monitoring method based on sensing fiber cloth in the above embodiments, this application embodiment can provide a storage medium for implementation. This storage medium stores a computer program; when executed by a processor, the computer program implements any of the monitoring methods based on sensing fiber cloth in the above embodiments.

[0150] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0151] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0152] Those skilled in the art should understand that the technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments have been described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0153] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A sensing fiber cloth, characterized in that, include: A fiber fabric matrix and a nanomaterial functional layer, wherein the nanomaterial functional layer is formed on the fiber fabric matrix by surface deposition; The nanomaterial functional layer includes a piezoresistive sensing unit and a piezoelectric sensing unit; The warp yarns of the fiber fabric matrix are conductive warp yarns; The conductive warp yarn is a shared signal transmission channel for the piezoresistive sensing unit and the piezoelectric sensing unit. The weft yarn of the fiber cloth matrix is ​​an insulating weft yarn; the piezoresistive sensing unit and the piezoelectric sensing unit are both arranged on the insulating weft yarn; The piezoresistive sensing unit is used to transmit resistance change signals via the conductive warp yarns to monitor the curing state of the polymer matrix and sense structural strain; the curing state of the polymer matrix refers to the curing state of the polymer matrix injected into the mold on which the sensing fiber cloth is laid during the preparation of the composite material structure; the composite material structure includes the sensing fiber cloth and the polymer matrix; The piezoelectric sensing unit is used to locate the damage location of the composite material structure.

2. The sensing fiber cloth according to claim 1, characterized in that, The nanomaterials in the functional layer are selected from at least one of graphene, carbon nanotubes, carbon black, lead zirconate titanate nanoparticles, barium titanate nanoparticles, and zinc oxide nanowires.

3. A method for preparing a sensing fiber cloth, characterized in that, The sensing fiber cloth is the sensing fiber cloth according to any one of claims 1 to 2, comprising: The fiber fabric matrix is ​​cleaned and chemically activated, and then treated with a silane coupling agent to obtain a pretreated fiber fabric matrix; the warp yarns of the fiber fabric matrix are conductive warp yarns. A nanomaterial functional layer is formed on the pretreated fiber cloth substrate by aerosol printing deposition process; the nanomaterial functional layer includes a piezoresistive sensing unit and a piezoelectric sensing unit. The fiber cloth substrate with the nanomaterial functional layer deposited is post-processed to obtain the sensing fiber cloth.

4. The method for preparing the sensing fiber cloth according to claim 3, characterized in that, The post-processing of the fiber cloth substrate with the deposited nanomaterial functional layer to obtain the sensing fiber cloth includes: The piezoresistive sensing unit in the fiber cloth matrix with the nanomaterial functional layer deposited is subjected to heat treatment, and the piezoelectric sensing unit in the fiber cloth matrix is ​​subjected to polarization treatment to obtain the sensing fiber cloth.

5. A monitoring method based on sensing fiber cloth, characterized in that, include: Based on the curing process of the sensing fiber cloth and polymer matrix, the mapping relationship between the degree of curing and the rate of change of resistance was obtained; The sensing fiber cloth is the sensing fiber cloth according to any one of claims 1 to 2; the resistance change rate is obtained by measuring the test resistance value of the piezoresistive sensing unit of the sensing fiber cloth based on the conductive warp yarns of the sensing fiber cloth. During the composite material structure preparation stage, based on the mapping relationship and the actual resistance value of the piezoresistive sensing unit measured during the preparation process, the curing process of the composite material structure is monitored to obtain curing monitoring results; the composite material structure includes the sensing fiber cloth and the polymer matrix; Tensile tests were performed on the obtained composite material structure specimens, and the sensitivity coefficient was obtained by using a standard resistance strain gauge as a reference. Based on the aforementioned sensitivity coefficient and the resistance value of the piezoresistive sensing unit of the sensing fiber cloth measured during the application of the composite material structure, the strain distribution of the composite material structure is evaluated to obtain the strain distribution evaluation result. Based on the piezoelectric sensing unit of the sensing fiber cloth in the composite material structure, the damage localization result of the composite material structure is obtained. Based on the solidification monitoring results, the strain distribution assessment results, and the damage localization results, full life cycle monitoring results are generated.

6. The monitoring method based on sensing fiber cloth according to claim 5, characterized in that, The curing process based on the sensing fiber cloth and polymer matrix obtains the mapping relationship between the degree of curing and the rate of change of resistance, including: The sensing fiber cloth is laid into the mold to form a composite material preform sample; Injecting the same type of polymer matrix as used in the preparation process into the composite preform sample; The degree of curing of the polymer matrix at different times during the curing process is measured, and the rate of change of the test resistance value of the piezoresistive sensing unit measured through the conductive warp is obtained. Based on the degree of curing and the rate of change of resistance value at the same time, the mapping relationship between the degree of curing and the rate of change of resistance value is obtained.

7. The monitoring method based on sensing fiber cloth according to claim 5, characterized in that, The tensile test is performed on the obtained composite material structure specimen, and the sensitivity coefficient is obtained with reference to a standard resistance strain gauge, including: The obtained composite material structure specimens are installed on a pre-set testing machine, and standard resistance strain gauges are attached to the surface of the composite material structure specimens. The composite material structure specimen is stretched at a preset speed using the testing machine, and the strain value of the standard resistance strain gauge and the resistance change rate of the piezoresistive sensing unit measured by a pair of adjacent conductive warp yarns of the sensing fiber cloth are recorded simultaneously to obtain the relationship curve between the strain value and the resistance change rate; based on the relationship curve, the sensitivity coefficient is obtained.

8. The monitoring method based on sensing fiber cloth according to claim 5, characterized in that, The piezoelectric sensing unit based on the sensing fiber cloth in the composite material structure obtains the damage localization result of the composite material structure, including: From the piezoelectric sensing units of the sensing fiber cloth in the composite material structure, a target excitation piezoelectric sensing unit is selected, and the other piezoelectric sensing units other than the target excitation piezoelectric sensing unit are used as receiving piezoelectric sensing units. An electrical signal is applied to the target excitation piezoelectric sensing unit through the conductive warp yarn, thereby exciting the target excitation piezoelectric sensing unit to emit ultrasonic guided wave signals, and multiple ultrasonic guided wave signal characteristics propagated through the composite material structure are captured by multiple receiving piezoelectric sensing units. Based on the characteristics of multiple ultrasonic guided wave signals, the coordinate position of the target excitation piezoelectric sensing unit, and the coordinate position of the receiving piezoelectric sensing unit, the damage localization result of the composite material structure is obtained.

9. The monitoring method based on sensing fiber cloth according to claim 8, characterized in that, The damage localization result of the composite material structure is obtained based on the characteristics of multiple ultrasonic guided wave signals, the coordinate position of the target excitation piezoelectric sensing unit, and the coordinate position of the receiving piezoelectric sensing unit, including: Based on the characteristics of multiple ultrasonic guided wave signals, the coordinate position of the target excitation piezoelectric sensing unit, and the coordinate position of the receiving piezoelectric sensing unit, multiple damage imaging maps are obtained according to the delay summation imaging algorithm. Multiple damage images are superimposed using an image fusion method to obtain the damage localization result of the composite material structure.

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